Sharif Digital Repository

Motion estimation and compensation is an essential part of existing video coding systems. Compared to the widely used block-matching algorithms (BMA), the mesh-based motion estimation (MME) produces better subjective and objective qualified image sequences in many cases, especially at low bitrates. However, the iterative refinement step of the MME is computationally too expensive. In this paper, we propose a fast MME scheme, which adjusts its interpolation patterns to the motion features of image sequences to achieve higher quality reconstructed results. Experimental results show notable rate-distortion improvement over both the BMA and the conventional non-iterative MME schemes, especially... 

The ARMA filtered fractionally differenced Gaussian Noise (FdGn) model and a new AR Filtered FdGn Added up model are applied to speech signal and performance of their parameters on speech Unvoiced/Voiced/Mixed/Silence classification is evaluated against Zero Crossing Rate (ZCR) feature. For parameter estimation of AR filtered FdGn model two methods were applied: iterative Maximum Likelihood (ML) method of Tewfik and a new computationally efficient Linear Minimum Square Error (LMSE) algorithm Also for parameters estimation of new Added up model two approaches were implemented: an Expectation-Maximization (EM) based approach and an iterative MSE approach. The described models and methods were... 

In this paper, we consider the problem of multiuser detection in the presence of users with unknown signature codes for a synchronous coded CDMA system. Interference suppression for unknown users is done by projecting the received signal on the null space of known users and then using eigenvalue decomposition and subspace techniques to derive a detector that cancels the known interference and successfully mitigates the unknown interference. Significant performance gains over detectors that ignore unknown users and treats them as noise is achieved. © 2001 IEEE  

This paper studies the problem of Simultaneous Sparse Approximation (SSA). This problem arises in many applications that work with multiple signals maintaining some degree of dependency, e.g., radar and sensor networks. We introduce a new method towards joint recovery of several independent sparse signals with the same support. We provide an analytical discussion of the convergence of our method, called Simultaneous Iterative Method (SIM). In this study, we compared our method with other group-sparse reconstruction techniques, namely Simultaneous Orthogonal Matching Pursuit (SOMP) and Block Iterative Method with Adaptive Thresholding (BIMAT), through numerical experiments. The simulation... 

A dictionary learning algorithm learns a set of atoms from some training signals in such a way that each signal can be approximated as a linear combination of only a few atoms. Most dictionary learning algorithms use a two-stage iterative procedure. The first stage is to sparsely approximate the training signals over the current dictionary. The second stage is the update of the dictionary. In this paper we develop some atom-by-atom dictionary learning algorithms, which update the atoms sequentially. Specifically, we propose an efficient alternative to the well-known K-SVD algorithm, and show by various experiments that the proposed algorithm is much faster than K-SVD while its results are... 

A new algorithm for the solution of multimaterial topology optimization problems is introduced in the present study. The presented method is based on the splitting of a multiphase topology optimization problem into a series of binary phase topology optimization sub-problems which are solved partially, in a sequential manner, using a traditional binary phase topology optimization solver; internal solver. The coupling between these incomplete solutions is ensured using an outer iteration strategy based on the block coordinate descend method. The presented algorithm provides a general framework to extend the traditional binary phase topology optimization solvers for the solution of multiphase... 

Discrete kinematic synthesis of discretely actuated hyper-redundant manipulators is a new practical problem in robotics. The problem concerns with determining the type of each manipulator module from among several specific types, so that the manipulator could reach several specified target frames with the lowest error. This paper suggests using a breadth-first search method and a workspace mean frame to solve this problem. To reduce errors, two heuristic ideas are proposed: two-by-two searching method and iteration. The effectiveness of the proposed method is verified through several numerical problems  

Array Thinning is the procedure of reducing the number of elements in such a way that leads to low sidelobe level and narrow beamwidth. Main motivations of array thinning are reduction in weight and cost of antennas array. W.P.M.N. Keizer has presented a new approach for the synthesis of thinned uniformly spaced linear arrays featuring a minimum sidelobe level. The method is based on the iterative Fourier technique to derive element excitations from the prescribed array factor using successive forward and backward Fourier transforms. Array thinning is accomplished by setting the amplitudes of the largest element excitations to unity and the others to zero during each iteration cycle. In this... 

MIMO radar is the next generation radar which transmits arbitrary waveforms at each one of its apertures. It has been shown that the design of waveforms for MIMO radars in order to synthesize a desired spatial beampattern is mapped into a waveform correlation matrix R design in the narrowband case. As of now, given a desired beampattern or estimated locations information of targets, calculating R has been modeled as an optimization problem like semi-definite programming. Also, in some special cases like rectangular beampattern, closed-form solutions for R has been proposed. In this paper, we introduce a fast algorithm which is capable of designing R in order to achieve more arbitrary... 

We consider a market in which two competing sellers offer two similar products on a social network. In this market, each agent chooses iteratively between the products based on her neighbors reactions and prices. This introduces two games: one between the agents and one between the sellers. We show that the first game is a full potential game and provide an algorithm to compute its convergence point. We also study various properties of the second game such as its equilibrium points and convergence  

Nowadays, we are facing epidemic spreading in many different areas; examples are infection propagation, rumor spreading and computer viruses in computer networks. Finding a strategy to control and mitigate the spread of these epidemics is gaining much interest in recent researches. Due to limitation of immunization resources, it is important to establish a strategy for selecting nodes which has the most effect in mitigating epidemics. In this paper, we propose a new algorithm that minimizes the worst expected growth of an epidemic by reducing the size of the largest connected component of the underlying contact network. The proposed algorithm is applicable to any level of available resources... 

In this paper, we propose a new method for impulsive noise removal from images. It uses the sparsity of natural images when they are expanded by mean of a good learned dictionary. The zeros in sparse domain give us an idea to reconstruct the pixels that are corrupted by random-value impulse noises. This idea comes from this reality that noisy image in sparse domain of original image will not have a sparse representation as much as original image sparsity. In this method we assume that the proper dictionary to achieve image in sparse domain is available  

The aim of this paper is to apply an Extended Kantorovich method (EKM) to simulate the static deflection of microplates under capillary force. The model accounts for the capillary force nonlinearity of the excitation. Starting from a one term Galerkin approximation and following the Extended Kantorovich procedure, the equations governing the microplate deflection are obtained. These equations are then solved iteratively with a rapid convergence procedure to yield the desired solution. The effects of capillary force on the pull-in phenomenon of microplates are delineated in some figures. It is shown that rapid convergence, high precision and independency of initial guess function makes the... 

In this paper a new iterative method is used to convert analog signals to digital (A/D) using sigma delta modulator (SDM). If intelligent reconstruction technique is used for decoding, either signals with higher bandwidth can be digitized or simpler circuitry can be utilized. An optimal family of SDM has recently been devised in order to improve performance of A/D converters. In this work, we improve performance of A/D converters even more, by combining this optimal family of SDM with iterative methods  

Noise interference and data loss are two major problems that affect the processing results of image data transmission and storage. Restoration of the lost information of an image based on the existing information is the essence of inpainting. In this paper a new algorithm based on Sample and Hold interpolation and Iteration is proposed for reconstructing damaged images from existing regions and is compared to some other methods. The experimental results show the superiority of the visual quality and PSNR performance of the proposed method. It is observed that this approach can efficiently fill in the holes with visually plausible information  

In this paper we extended a previously investigated modular method that is designed to compensate for interpolation distortions of one-dimensional signals, to two dimensions (2-D). Next the proposed 2-D modular technique was applied in an iterative fashion and was shown through both simulations and theoretical analyses to enhance the convergence of the iterative technique. In fact, with only a few modules we were able to achieve drastic improvements in signal reconstruction, and with a much less computational complexity. Moreover, both the simulations and the theoretical analysis confirmed the robustness of the proposed scheme against additive noise  

In distribution system planning studies, reliability evaluation is performed during optimization procedure to calculate the interruption cost, DISCO's income and to check the viability of constraints related to reliability indices. In each iteration of the optimization algorithm a special plan is evaluated that is different from other plans. So the configuration and specification of the network which is one of the input information for reliability evaluation is changing continuously that makes difficulties for this evaluation. To solve these difficulties, this paper presents a systematic method for reliability evaluation in distribution planning studies. The proposed approach can be... 

In this paper, we address recovery of sparse signals from compressed measurements, and sparse signal approximation, which have received considerable attention over the last decade. First, we revisit smoothed L0 (SL0), a well-known sparse recovery algorithm, and give some insights into it that have not been noticed previously. Specifically, we re-derive the SL0 algorithm based on proximal methods, and using recent results in solving nonconvex problems by proximal algorithms, we provide a convergence guarantee for it. In addition, inspired by this derivation, we propose a general family of algorithms, which we call iterative sparsification-projection (ISP), having SL0 as a special member. Our... 

In the present study, the neutron noise, i.e. the stationary fluctuation of the neutron flux around its mean value is calculated based on the 2G, 3D neutron diffusion theory. To this end, the static neutron calculation is performed at the first stage. The spatial discretization of the neutron diffusion equation is performed based on linear approximation of Galerkin Finite Element Method (GFEM) using unstructured tetrahedron elements. Using power iteration method, neutron flux and corresponding eigen-value are obtained. The results are then benchmarked against the valid results for VVER-1000 (3D) benchmark problem. In the second stage, the neutron noise equation is solved using GFEM and...